Home > Documents in Process > Rare genetic variants influence regional cortical and subcortical grey matter volumes in genetic frontotemporal dementia: A GENFI Study > print

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024 7 _ |a 10.1002/alz70856_106121
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024 7 _ |a pmid:41505495
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024 7 _ |a 1552-5260
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024 7 _ |a 1552-5279
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037 _ _ |a DZNE-2026-00052
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Mirza, Saira S
|b 0
111 2 _ |a Alzheimer’s Association International Conference
|g AAIC 25
|c Toronto
|d 2025-07-27 - 2025-07-31
|w Canada
245 _ _ |a Rare genetic variants influence regional cortical and subcortical grey matter volumes in genetic frontotemporal dementia: A GENFI Study
260 _ _ |c 2025
336 7 _ |a Abstract
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336 7 _ |a Conference Paper
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336 7 _ |a Journal Article
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520 _ _ |a There is substantial heterogeneity in clinical presentation of genetic Frontotemporal Dementia (FTD), even within the same family. This suggests that additional heritability may exist and contribute to this variable presentation. We examined whether gene-based aggregate burden of genome-wide rare variants (minor allele frequency [MAF]: ≤1%) contribute to variation in regional cortical and subcortical grey matter volumes, after controlling for effects of causative mutations in GRN, MAPT, and C9orf72.This study was embedded within the GENetic Frontotemporal dementia Initiative (GENFI), which recruits genetic FTD cases and their asymptomatic at-risk family members, both carriers and non-carriers of FTD mutations. We included 518 participants with genotype (Neurochip; imputed against TOPMed), and T1w-MRI brain volumetric data. Gene-based burden tests that aggregate the number of rare variants by gene were used to examine the association of rare variants (MAF: ≤1%) with regional cortical and subcortical grey matter volumes (70 regions of interest [ROIs]), controlling for age, sex, total intracranial volume, mutation status, scanner site, population stratification, and family membership (kinship matrix) using RVTests. Annotations for loss of function mutations (LOF): start gain, stop loss, start loss, essential splice site, stop gain, normal splice site, and non-synonymous. Multiple testing correction accounted for the number of genes and number of independent grey matter volumes as calculated by matSpD (p-value threshold: 0.05/(17,053x42) = 6.98 x10-8).Aggregate burden of LOF mutations (DNAJB8-AS1, WDR26, RDM1P5, BSND, CNOT2, DDA1, ASAH2B, PPM1A, HOXD13, ALDH1A1, CENATAC, ANKRD45) was associated with significantly lower volumes within the left temporal lobe (ROIs: left temporal and lateral temporal left), and greater volume in the putamen bilaterally (TSACC). All genes are protein coding, except the DNAJB8-AS1 (antisense RNA) and RDM1P5 (pseudogene), and are variably expressed in the brain. Molecular functions of significant genes involve regulation of gene expression, transcription, and cell cycle, ion channel function, and chromosomal segregation. WDR26 and CNOT2 genes have been implicated in neurodevelopment and neurological disorders respectively; BSND gene is involved in neurotransmission.Identification of deleterious or protective rare variants contributing to FTD imaging phenotypes may help identify genetic modifiers of familial FTD. Replication in larger cohorts is needed.
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650 _ 7 |a tau Proteins
|2 NLM Chemicals
650 _ 7 |a C9orf72 Protein
|2 NLM Chemicals
650 _ 7 |a Biomarkers
|2 NLM Chemicals
650 _ 7 |a Progranulins
|2 NLM Chemicals
650 _ 7 |a MAPT protein, human
|2 NLM Chemicals
650 _ 7 |a C9orf72 protein, human
|2 NLM Chemicals
650 _ 7 |a GRN protein, human
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Frontotemporal Dementia: genetics
|2 MeSH
650 _ 2 |a Frontotemporal Dementia: pathology
|2 MeSH
650 _ 2 |a Frontotemporal Dementia: diagnostic imaging
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Gray Matter: pathology
|2 MeSH
650 _ 2 |a Gray Matter: diagnostic imaging
|2 MeSH
650 _ 2 |a tau Proteins: genetics
|2 MeSH
650 _ 2 |a Mutation: genetics
|2 MeSH
650 _ 2 |a C9orf72 Protein: genetics
|2 MeSH
650 _ 2 |a Biomarkers
|2 MeSH
650 _ 2 |a Progranulins: genetics
|2 MeSH
650 _ 2 |a Brain: pathology
|2 MeSH
650 _ 2 |a Brain: diagnostic imaging
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Genome-Wide Association Study
|2 MeSH
650 _ 2 |a Genotype
|2 MeSH
700 1 _ |a Pasternak, Maurice
|b 1
700 1 _ |a Paterson, Andrew D
|b 2
700 1 _ |a Tartaglia, Carmela
|b 3
700 1 _ |a Black, Sandra E
|b 4
700 1 _ |a Mitchell, Sara
|b 5
700 1 _ |a Freedman, Morris
|b 6
700 1 _ |a Tang-Wai, David F
|b 7
700 1 _ |a Rogaeva, Ekaterina
|b 8
700 1 _ |a Cash, David M
|b 9
700 1 _ |a Bocchetta, Martina
|b 10
700 1 _ |a van Swieten, John
|b 11
700 1 _ |a Laforce, Robert
|b 12
700 1 _ |a Tagliavini, Fabrizio
|b 13
700 1 _ |a Borroni, Barbara
|b 14
700 1 _ |a Galimberti, Daniela
|b 15
700 1 _ |a Rowe, James B
|b 16
700 1 _ |a Graff, Caroline
|b 17
700 1 _ |a Finger, Elizabeth
|b 18
700 1 _ |a Sorbi, Sandro
|b 19
700 1 _ |a Mendonca, Alexandre
|b 20
700 1 _ |a Butler, Christopher R
|b 21
700 1 _ |a Gerhard, Alexander
|b 22
700 1 _ |a Sánchez-Valle, Raquel
|b 23
700 1 _ |a Moreno, Fermin
|b 24
700 1 _ |a Synofzik, Matthis
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700 1 _ |a Vandenberghe, Rik
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700 1 _ |a Ducharme, Simon
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700 1 _ |a Levin, Johannes
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700 1 _ |a Otto, Markus
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700 1 _ |a Santana, Isabel
|b 30
700 1 _ |a Rohrer, Jonathan D
|b 31
700 1 _ |a Masellis, Mario
|b 32
773 _ _ |a 10.1002/alz70856_106121
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